RAG Evaluation Metrics: A Practical Guide for Measuring Retrieval-Augmented Generation with Maxim AI
Why this matters if you own a RAG feature
I’ve watched clean lab demos fall apart in production: the retriever brings back the wrong paragraph when a user types shorthand, the model fills gaps with confident fiction, and p95 latency creeps past your SLA the second traffic spikes. This guide is the pragmatic way I measure and stabilize RAG—so we ship fast, and earn trust.
If you need rails for this, start here:
Experiment and compare retrievers, prompts, chunking: Experimentation
Simulate real users and evaluate agents at scale: Agent Simulation & Evaluation
Trace, monitor, and alert on live quality: Agent Observability
Docs and SDKs to wire it in: Docs, SDK Overview
If you want a walkthrough: Book a Demo or Get started free
The short list I actually track
Retrieval re…
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